The CONFIDENT-P trial: Clinical implementation of artificial intelligence assistance in prostate cancer pathology
TPS405Background: Prostate cancer grading has been subject to variation, putting patients at risk for over- and under-treatment (Flach et al., 2022). As a response, development of artificial intelligence (AI) prostate cancer algorithms has been on the rise in the field of pathology. Despite promisin...
        Saved in:
      
    
          | Published in | Journal of clinical oncology Vol. 41; no. 6_suppl; p. TPS405 | 
|---|---|
| Main Authors | , , , , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
            American Society of Clinical Oncology
    
        20.02.2023
     | 
| Online Access | Get full text | 
| ISSN | 0732-183X 1527-7755  | 
| DOI | 10.1200/JCO.2023.41.6_suppl.TPS405 | 
Cover
| Abstract | TPS405Background: Prostate cancer grading has been subject to variation, putting patients at risk for over- and under-treatment (Flach et al., 2022). As a response, development of artificial intelligence (AI) prostate cancer algorithms has been on the rise in the field of pathology. Despite promising results in retrospective studies, and several FDA-approved and CE-IVD certified algorithms on the market, prospective clinical implementation studies of AI are lacking. Moreover, uptake of digital pathology is currently insufficient due to high implementation costs (Ho et al., 2014). In this trial, we will explore the benefits of an AI-assisted pathology workflow in prostate cancer detection, while maintaining diagnostic safety standards. We will focus on reducing costly immunohistochemistry stains (IHC), which are currently used to aid in the diagnosis of prostate cancer. Methods: CONFIDENT-P is a SPIRIT-AI compliant single-centre, clinical trial, in a fully digital academic pathology laboratory. We will prospectively enroll 80 prostate cancer patients who undergo prostate needle biopsies. The pathology specimens will be pseudo-randomized to be assessed by a pathologist with- or without AI-assistance in a pragmatic (bi-)weekly sequential design, in a 1:1 allocation ratio. Patients are excluded when they are redirected for a second opinion to the UMC Utrecht. In the intervention group, pathologists will assess whole slide images (WSI) of the standard haematoxylin-eosin (HE)-stained sections assisted by the output of a CE-IVD approved prostate cancer detection and grading algorithm. In the control group, pathologists will assess HE WSI according to the current clinical workflow. If no tumour cells are identified or when the pathologist is in doubt, staining by immunohistochemistry (IHC) will be performed. Primary endpoint is the number of saved resources on IHC for detecting tumour cells, since this will clarify tangible cost savings that will help to build the business case for AI. We will compare the proportion of IHC-use in both arms, and calculate adjusted relative risks, using a log-binomial model. The sample size gives at least 80% power to detect a 30% difference in IHC usage, using a one-sided significance level of 5%. Enrolment is set to begin in November 2022. The ethics committee (MREC NedMec) waived the need of official ethical approval, as participants are not subjected to procedures and as they are not required to follow rules. Furthermore, they are not at risk of an inferior diagnosis. Trial registration is therefore applicable nor suitable. | 
    
|---|---|
| AbstractList | TPS405Background: Prostate cancer grading has been subject to variation, putting patients at risk for over- and under-treatment (Flach et al., 2022). As a response, development of artificial intelligence (AI) prostate cancer algorithms has been on the rise in the field of pathology. Despite promising results in retrospective studies, and several FDA-approved and CE-IVD certified algorithms on the market, prospective clinical implementation studies of AI are lacking. Moreover, uptake of digital pathology is currently insufficient due to high implementation costs (Ho et al., 2014). In this trial, we will explore the benefits of an AI-assisted pathology workflow in prostate cancer detection, while maintaining diagnostic safety standards. We will focus on reducing costly immunohistochemistry stains (IHC), which are currently used to aid in the diagnosis of prostate cancer. Methods: CONFIDENT-P is a SPIRIT-AI compliant single-centre, clinical trial, in a fully digital academic pathology laboratory. We will prospectively enroll 80 prostate cancer patients who undergo prostate needle biopsies. The pathology specimens will be pseudo-randomized to be assessed by a pathologist with- or without AI-assistance in a pragmatic (bi-)weekly sequential design, in a 1:1 allocation ratio. Patients are excluded when they are redirected for a second opinion to the UMC Utrecht. In the intervention group, pathologists will assess whole slide images (WSI) of the standard haematoxylin-eosin (HE)-stained sections assisted by the output of a CE-IVD approved prostate cancer detection and grading algorithm. In the control group, pathologists will assess HE WSI according to the current clinical workflow. If no tumour cells are identified or when the pathologist is in doubt, staining by immunohistochemistry (IHC) will be performed. Primary endpoint is the number of saved resources on IHC for detecting tumour cells, since this will clarify tangible cost savings that will help to build the business case for AI. We will compare the proportion of IHC-use in both arms, and calculate adjusted relative risks, using a log-binomial model. The sample size gives at least 80% power to detect a 30% difference in IHC usage, using a one-sided significance level of 5%. Enrolment is set to begin in November 2022. The ethics committee (MREC NedMec) waived the need of official ethical approval, as participants are not subjected to procedures and as they are not required to follow rules. Furthermore, they are not at risk of an inferior diagnosis. Trial registration is therefore applicable nor suitable. TPS405 Background: Prostate cancer grading has been subject to variation, putting patients at risk for over- and under-treatment (Flach et al., 2022). As a response, development of artificial intelligence (AI) prostate cancer algorithms has been on the rise in the field of pathology. Despite promising results in retrospective studies, and several FDA-approved and CE-IVD certified algorithms on the market, prospective clinical implementation studies of AI are lacking. Moreover, uptake of digital pathology is currently insufficient due to high implementation costs (Ho et al., 2014). In this trial, we will explore the benefits of an AI-assisted pathology workflow in prostate cancer detection, while maintaining diagnostic safety standards. We will focus on reducing costly immunohistochemistry stains (IHC), which are currently used to aid in the diagnosis of prostate cancer. Methods: CONFIDENT-P is a SPIRIT-AI compliant single-centre, clinical trial, in a fully digital academic pathology laboratory. We will prospectively enroll 80 prostate cancer patients who undergo prostate needle biopsies. The pathology specimens will be pseudo-randomized to be assessed by a pathologist with- or without AI-assistance in a pragmatic (bi-)weekly sequential design, in a 1:1 allocation ratio. Patients are excluded when they are redirected for a second opinion to the UMC Utrecht. In the intervention group, pathologists will assess whole slide images (WSI) of the standard haematoxylin-eosin (HE)-stained sections assisted by the output of a CE-IVD approved prostate cancer detection and grading algorithm. In the control group, pathologists will assess HE WSI according to the current clinical workflow. If no tumour cells are identified or when the pathologist is in doubt, staining by immunohistochemistry (IHC) will be performed. Primary endpoint is the number of saved resources on IHC for detecting tumour cells, since this will clarify tangible cost savings that will help to build the business case for AI. We will compare the proportion of IHC-use in both arms, and calculate adjusted relative risks, using a log-binomial model. The sample size gives at least 80% power to detect a 30% difference in IHC usage, using a one-sided significance level of 5%. Enrolment is set to begin in November 2022. The ethics committee (MREC NedMec) waived the need of official ethical approval, as participants are not subjected to procedures and as they are not required to follow rules. Furthermore, they are not at risk of an inferior diagnosis. Trial registration is therefore applicable nor suitable.  | 
    
| Author | Flach, Rachel ter Hoeve, Natalie D van Dooijeweert, Carmen Stathonikos, Nikolas van Diest, Paul J. Nguyen, Tri  | 
    
| Author_xml | – sequence: 1 givenname: Rachel surname: Flach fullname: Flach, Rachel – sequence: 2 givenname: Nikolas surname: Stathonikos fullname: Stathonikos, Nikolas – sequence: 3 givenname: Tri surname: Nguyen fullname: Nguyen, Tri – sequence: 4 givenname: Natalie D surname: ter Hoeve fullname: ter Hoeve, Natalie D – sequence: 5 givenname: Paul J. surname: van Diest fullname: van Diest, Paul J. – sequence: 6 givenname: Carmen surname: van Dooijeweert fullname: van Dooijeweert, Carmen  | 
    
| BookMark | eNqNkNFKwzAUhoNMcJu-Q_C-NWmapNuFIHXTydgGVvAupFm6RbO2Jhljb2_LfAAvDuf85_D_HL4RGNRNrQG4xyjGCUIPb_k6TlBC4hTHTPhj29q42LyniF6BIaYJjzindACGiJMkwhn5vAEj778QwmlG6BD8FHsN8_VqvnierYpoA4Mz0k5hbk1tlLTQHFqrD7oOMpimhk0FpQumMsr0xzpoa81O10pD6b3xQfajqWHrmk4EDVW_cbCVYd_YZne-BdeVtF7f_fUx-JjPivw1Wq5fFvnTMlIYMRpxpcokQ1QyhDKESEZ5qSZMdbVlivFKs5IRPME8TSuUpYRUTJXbsiKcSpxKMgbTS67qPvFOV6J15iDdWWAkeniigyd6eCLF4g-euMDrzI8X86mxQTv_bY8n7cReSxv2_wn4BXkQffg | 
    
| ContentType | Journal Article | 
    
| Copyright | 2023 by American Society of Clinical Oncology | 
    
| Copyright_xml | – notice: 2023 by American Society of Clinical Oncology | 
    
| DBID | AAYXX CITATION  | 
    
| DOI | 10.1200/JCO.2023.41.6_suppl.TPS405 | 
    
| DatabaseName | CrossRef | 
    
| DatabaseTitle | CrossRef | 
    
| DatabaseTitleList | CrossRef  | 
    
| DeliveryMethod | fulltext_linktorsrc | 
    
| Discipline | Medicine Pharmacy, Therapeutics, & Pharmacology  | 
    
| EISSN | 1527-7755 | 
    
| EndPage | TPS405 | 
    
| ExternalDocumentID | 10_1200_JCO_2023_41_6_suppl_TPS405 396242  | 
    
| Genre | meeting-report | 
    
| GrantInformation_xml | – fundername: Paige | 
    
| GroupedDBID | --- .55 0R~ 18M 2WC 34G 39C 4.4 53G 5GY 5RE 8F7 AAQQT AARDX AAWTL AAYEP ABJNI ABOCM ACGFO ACGFS ACGUR ADBBV AEGXH AENEX AIAGR ALMA_UNASSIGNED_HOLDINGS BAWUL BYPQX C45 CS3 DIK EBS EJD F5P F9R FBNNL FD8 GX1 HZ~ IH2 IPNFZ K-O KQ8 L7B LSO MJL N9A O9- OK1 OVD OWW P2P QTD R1G RHI RIG RLZ RUC SJN TEORI TR2 TWZ UDS VVN WH7 X7M YFH YQY AAYXX ABBLC CITATION  | 
    
| ID | FETCH-LOGICAL-c1065-7ccb2805a6008003857bc96cc96d6c67fe6b63191744f08433f6cbdbf375a14a3 | 
    
| ISSN | 0732-183X | 
    
| IngestDate | Tue Jul 01 00:40:48 EDT 2025 Wed Apr 16 02:14:36 EDT 2025  | 
    
| IsPeerReviewed | true | 
    
| IsScholarly | true | 
    
| Issue | 6_suppl | 
    
| Language | English | 
    
| LinkModel | OpenURL | 
    
| MergedId | FETCHMERGED-LOGICAL-c1065-7ccb2805a6008003857bc96cc96d6c67fe6b63191744f08433f6cbdbf375a14a3 | 
    
| Notes | Abstract Disclosures | 
    
| ParticipantIDs | crossref_primary_10_1200_JCO_2023_41_6_suppl_TPS405 wolterskluwer_health_10_1200_JCO_2023_41_6_suppl_TPS405  | 
    
| ProviderPackageCode | CITATION AAYXX  | 
    
| PublicationCentury | 2000 | 
    
| PublicationDate | 20230220 2023-02-20  | 
    
| PublicationDateYYYYMMDD | 2023-02-20 | 
    
| PublicationDate_xml | – month: 2 year: 2023 text: 20230220 day: 20  | 
    
| PublicationDecade | 2020 | 
    
| PublicationTitle | Journal of clinical oncology | 
    
| PublicationTitleAbbrev | ASCO MEETING ABSTRACTS | 
    
| PublicationYear | 2023 | 
    
| Publisher | American Society of Clinical Oncology | 
    
| Publisher_xml | – name: American Society of Clinical Oncology | 
    
| SSID | ssj0014835 | 
    
| Score | 2.417661 | 
    
| Snippet | TPS405Background: Prostate cancer grading has been subject to variation, putting patients at risk for over- and under-treatment (Flach et al., 2022). As a... TPS405 Background: Prostate cancer grading has been subject to variation, putting patients at risk for over- and under-treatment (Flach et al., 2022). As a...  | 
    
| SourceID | crossref wolterskluwer  | 
    
| SourceType | Index Database Publisher  | 
    
| StartPage | TPS405 | 
    
| Title | The CONFIDENT-P trial: Clinical implementation of artificial intelligence assistance in prostate cancer pathology | 
    
| URI | https://ovidsp.ovid.com/ovidweb.cgi?T=JS&NEWS=n&CSC=Y&PAGE=fulltext&D=ovft&DO=10.1200/JCO.2023.41.6_suppl.TPS405 | 
    
| Volume | 41 | 
    
| hasFullText | 1 | 
    
| inHoldings | 1 | 
    
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVAFT databaseName: Open Access Digital Library customDbUrl: eissn: 1527-7755 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0014835 issn: 0732-183X databaseCode: KQ8 dateStart: 19990101 isFulltext: true titleUrlDefault: http://grweb.coalliance.org/oadl/oadl.html providerName: Colorado Alliance of Research Libraries – providerCode: PRVBFR databaseName: Free Medical Journals customDbUrl: eissn: 1527-7755 dateEnd: 20241102 omitProxy: true ssIdentifier: ssj0014835 issn: 0732-183X databaseCode: DIK dateStart: 20040101 isFulltext: true titleUrlDefault: http://www.freemedicaljournals.com providerName: Flying Publisher – providerCode: PRVFQY databaseName: GFMER Free Medical Journals customDbUrl: eissn: 1527-7755 dateEnd: 20241102 omitProxy: true ssIdentifier: ssj0014835 issn: 0732-183X databaseCode: GX1 dateStart: 20040101 isFulltext: true titleUrlDefault: http://www.gfmer.ch/Medical_journals/Free_medical.php providerName: Geneva Foundation for Medical Education and Research  | 
    
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3db9MwELfKkBASQjBAG1_yA9oLS0liJ254Q92qDlhaQSb1LYqdhFUbLfQDVP5i_gzuYjtJNZDGHhpZjmI5vV_Od_bd7wh5JbgUufDgSwN_w-E9VzoyyguHF6EMsjxypcQT3dM4HJ7x95Ng0un8bkUtrVeyq379Na_kJlKFPpArZsn-h2TrQaED2iBfuIKE4XptGfdH8eDk6DhOnPHrqgQH-vh9m-84_Wrjw61liMMY1ohpm44TjGg0JbE5rcK2qlQjDApTxQLpV8-bDfirxmydYDmfqa2N-sFlpotNfULm6DqcA23cc1AnFzrKL4bGZVab9_GX9Uarw2QxtZ3I5jicFz8KvSggc2Nh4pXNroXPqixwt8GZPY6ysakYe2JnOmrPVKtCwXwHlM9Er1pGVfsCfANN8mt1uSbRMpgN0yVWRm2p52T8mbtBa7FvOq4sJb6ukt0fdXH-Xe51zXjd9iht_u54lI6PBunHk_jD9k1tLkSYinOL3PZh_amKjEzqYCTwSXUpWPuehh4X5vDm3zPYMqXu_ZxjeMXyosquaNlIyQNy3-CBvtNIfUg6xWyX3Dk14Ru75GCsidI3hzRp8v6Wh_SAjhsK9c0j8h1u0xayaYXst9QKj27jms5L2uCatnFNG1xDP7W4phrXtMb1Y3I2OE76Q8cUB3EUaJXAEUpJv-cGWVg5PawXCKmiUMEvD1UoSlA2IcPdCM5Lt8cZK0Mlc1kyEWQez9gTsjObz4o9QsGHAbsgB0sc86pZGPllIIT0WFBEUil_nzD7P6ffNAdMir6zjwfB_VGK0km5lxrppFo6-0RsiSTVic3XePLpjZ98Ru42H9tzsrNarIsXYDSv5MsKb38A9TDGvg | 
    
| linkProvider | Geneva Foundation for Medical Education and Research | 
    
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=The+CONFIDENT-P+trial%3A+Clinical+implementation+of+artificial+intelligence+assistance+in+prostate+cancer+pathology&rft.jtitle=Journal+of+clinical+oncology&rft.au=Flach%2C+Rachel&rft.au=Stathonikos%2C+Nikolas&rft.au=Nguyen%2C+Tri&rft.au=ter+Hoeve%2C+Natalie+D&rft.date=2023-02-20&rft.pub=American+Society+of+Clinical+Oncology&rft.issn=0732-183X&rft.eissn=1527-7755&rft.volume=41&rft.issue=6_suppl&rft.spage=TPS405&rft.epage=TPS405&rft_id=info:doi/10.1200%2FJCO.2023.41.6_suppl.TPS405&rft.externalDBID=NO_PDF_LINK&rft.externalDocID=396242 | 
    
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0732-183X&client=summon | 
    
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0732-183X&client=summon | 
    
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0732-183X&client=summon |